Docker Desktop: The vllm-metal inference backend in Docker Model Runner on macOS unconditionally sets trust_remote_code=True when loading model…
Summary
The vllm-metal inference backend in Docker Model Runner on macOS unconditionally sets trust_remote_code=True when loading model tokenizers, and runs without sandboxing. This causes transformers.AutoTokenizer.from_pretrained() to import and execute arbitrary Python files included in any model pulled from an OCI registry, resulting in arbitrary code execution on the Docker host as the Docker Desktop user when inference is triggered. Any container on the Docker network can trigger this by calling the model-runner.docker.internal API to pull a malicious model and request inference.
Mitigation
Mitigation steps weren't captured by the parser for this advisory — this is a parsing gap, not a statement that no fix exists. Read the vendor advisory below for the authoritative guidance.
Official advisory · medium-confidence parse· fetched 2 hours ago·verify at source
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